In general the content users would classify as news has many examples of viral spreading of content.
Twitter is sometimes considered to be a news source, with [1]} counting
at least 85% of tweets being related to headline news.
Much of which includes news of commercial interest and opens possibilities for real time engagement.
Real time monitoring of these events being discussed is therefore essential for automated
engagement. With spikes in topics lasting in the magnitude of minutes,
the run time of an algorithm should be reduced as much as possible and the ability
of the algorithm to utilize
the hardware of multiple processors is highly desirable .
The work of [2]}, [3]} discusses this real time monitoring of events and gives a number of case studies, comparing techniques for spike detection.
Our work has a slightly different emphasis, since we aim to detect nodes and edges that
facilitate propagation of information, and hence would be natural candidates for monitoring
and intervention.
